Development of a clinical applicable graphical user interface to automatically detect exercise oscillatory ventilation: The VOdEX-tool.

BACKGROUND: Cardiopulmonary exercise testing (CPET) gained importance in the prognostic assessment of especially patients with heart failure (HF). A meaningful prognostic parameter for early mortality in HF is exercise oscillatory ventilation (EOV). This abnormal respiratory pattern is recognized by hypo- and hyperventilation during CPET. Up until now, assessment of EOV is mainly done upon visual agreement or manual calculation. The purpose of this research was to automate the interpretation of EOV so this prognostic parameter could be readily investigated during CPET.

METHODS AND RESULTS: Preliminary, four definitions describing the original characteristics of EOV, were selected and integrated in the "Ventilatory Oscillations during Exercise-tool" (VOdEX-tool), a graphical user interface that allows automate calculation of EOV. A Discrete Meyer Level 2 wavelet transformation appeared to be the optimal filter to apply on the collected breath-by-breath minute ventilation CPET data. Divers aspects of the definitions i.e. cycle length, amplitude, regularity and total duration of EOV were combined and calculated. The oscillations meeting the criteria were visualised. Filter methods and cut-off criteria were made adjustable for clinical application and research. The VOdEX-tool was connected to a database.

CONCLUSIONS: The VOdEX-tool provides the possibility to calculate EOV automatically and to present the clinician an overview of the presence of EOV at a glance. The computerized analysis of EOV can be made readily available in clinical practice by integrating the tool in the manufactures existing CPET software. The VOdEX-tool enhances assessment of EOV and therefore contributes to the estimation of prognosis in especially patients with HF.